23 citations · 68 across the 6 of their papers we have counts for
5 papers · 1 filter
CLEANN: Accelerated Trojan Shield for Embedded Neural Networks
Mojan Javaheripi, Mohammad Samragh, Gregory Fields +2
We propose CLEANN, the first end-to-end framework that enables online mitigation of Trojans for embedded Deep Neural Network (DNN) applications. A Trojan attack works by injecting…
GeneCAI: Genetic Evolution for Acquiring Compact AI
Mojan Javaheripi, Mohammad Samragh, Tara Javidi +1
In the contemporary big data realm, Deep Neural Networks (DNNs) are evolving towards more complex architectures to achieve higher inference accuracy. Model compression techniques c…
ASCAI: Adaptive Sampling for acquiring Compact AI
Mojan Javaheripi, Mohammad Samragh, Tara Javidi +1
This paper introduces ASCAI, a novel adaptive sampling methodology that can learn how to effectively compress Deep Neural Networks (DNNs) for accelerated inference on resource-cons…
SWNet: Small-World Neural Networks and Rapid Convergence
Mojan Javaheripi, Bita Darvish Rouhani, Farinaz Koushanfar
Training large and highly accurate deep learning (DL) models is computationally costly. This cost is in great part due to the excessive number of trained parameters, which are well…
CodeX: Bit-Flexible Encoding for Streaming-based FPGA Acceleration of DNNs
Mohammad Samragh, Mojan Javaheripi, Farinaz Koushanfar
This paper proposes CodeX, an end-to-end framework that facilitates encoding, bitwidth customization, fine-tuning, and implementation of neural networks on FPGA platforms. CodeX in…